• Archives of design research
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• v.19 no.4 s.66
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• pp.121-132
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• 2006

In the Western Philosophy that was centered on reason, sense has been belittled as a low level of conception under reason. However, the 21st century modern visual environment pushes away the epistemology centered on reason and puts 'sensuality' and 'sense' on its place. Especially, public films are one of the fields that rapidly reflect such changes and lead the changes. However, unfortunately, it is difficult to find such efforts that reflect the artistic and aesthetic significance of sense from the public films. It is because that sense is considered superficial and somewhat not real, while recognizing sense as the low level of conception under reason over the long history. Given the fact, this study reviews the by Gilles Deleuze, a modern philosopher who gives a new value on sense, and it would be meaningful to analyze the works of Chris Cunningham who makes films with the concept of Gilles Deleuze. After we analyzed three music videos of Aphex Twin directed by Chris Cunningham, we can ascertain that the films are based on body without Oranges, hysteric, and diagram that are suggested from by Gilles Deleuze. Analyzing recently released films centered on 'sense' in a superficial manner that includes production method or picture composition, including the films of Chris Cunningham, falls into the error of overlooking the director's aesthetics. Understanding the modern logic of sense that is newly developing, studying its substance, and analyzing the films will make a sacrifice of suggesting a new alternative.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.40 no.1
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• pp.152-164
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• 2015

A rapid development of semiconductors, sensors and mobile network technologies has enable that the embedded device includes high sensitivity sensors, wireless communication modules and a video processing module for vehicular environment, and many researchers have been actively studying the smart car technology combined on the high performance embedded devices. The vehicle is increased as the development of society, and the risk of accidents is increasing gradually. Thus, the advanced driver assistance system providing the vehicular status and the surrounding environment of the vehicle to the driver using various sensor data is actively studied. In this paper, we design and implement the smart vehicular camera device providing the V2X communication and gathering environment information. And we studied the method to create the metadata from a received video data and sensor data using video analysis algorithm. In addition, we invent S-ROI, D-ROI methods that set a region of interest in a video frame to improve calculation performance. We performed the performance evaluation for two ROI methods. As the result, we confirmed the video processing speed that S-ROI is 3.0 times and D-ROI is 4.8 times better than a full frame analysis.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.10 no.6
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• pp.609-616
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• 2017

In this paper, we propose an algorithm to obtain more stable and high recognition rate by using left and right rotation information of input image in order to obtain a stable recognition rate in face recognition. The proposed algorithm uses the facial image as the input information in the web camera environment to reduce the size of the image and normalize the information about the brightness and color to obtain the improved recognition rate. We apply Principal Component Analysis (PCA) to the detected candidate regions to obtain feature vectors and classify faces. Also, In order to reduce the error rate range of the recognition rate, a set of data with the left and right $45^{\circ}$ rotation information is constructed considering the directionality of the input face image, and each feature vector is obtained with PCA. In order to obtain a stable recognition rate with the obtained feature vector, it is after scattered in the eigenspace and the final face is recognized by comparing euclidean distant distances to each feature. The PCA-based feature vector is low-dimensional data, but there is no problem in expressing the face, and the recognition speed can be fast because of the small amount of calculation. The method proposed in this paper can improve the safety and accuracy of recognition and recognition rate faster than other algorithms, and can be used for real-time recognition system.

• Journal of the Korean Society of Radiology
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• v.16 no.4
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• pp.453-462
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• 2022

In this paper, the artificial intelligence (AI) technology used in the medical image analysis field was analyzed through a literature review. Literature searches were conducted on PubMed, ResearchGate, Google and Cochrane Review using the key word. Through literature search, 114 abstracts were searched, and 98 abstracts were reviewed, excluding 16 duplicates. In the reviewed literature, AI is applied in classification, localization, disease detection, disease segmentation, and fit degree of registration images. In machine learning (ML), prior feature extraction and inputting the extracted feature values into the neural network have disappeared. Instead, it appears that the neural network is changing to a deep learning (DL) method with multiple hidden layers. The reason is thought to be that feature extraction is processed in the DL process due to the increase in the amount of memory of the computer, the improvement of the calculation speed, and the construction of big data. In order to apply the analysis of medical images using AI to medical care, the role of physicians is important. Physicians must be able to interpret and analyze the predictions of AI algorithms. Additional medical education and professional development for existing physicians is needed to understand AI. Also, it seems that a revised curriculum for learners in medical school is needed.

• The Journal of the Convergence on Culture Technology
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• v.9 no.5
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• pp.563-568
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• 2023

The government's strengthening of the standards for mentally ill patients and expanding the scope of examinations to the entire nation reflects the changing times. According to the OECD's announcement (2021), the incidence of depression and anxiety has more than doubled since the prolonged COVID-19 pandemic in countries around the world, with Korea's prevalence ranking first. However, only 12.1% of those who have been diagnosed with mental disorders received counseling and treatment from experts. The difference between depression and simple depression is significant depending on whether it is medically treated or temporary, but it can be seen that the continuation of depression is depression. In order to reduce this depression, Kandinsky's work was visualized and created. In a study conducted by changing the playback speed of the produced Kandinsky image, beta and gamma values, which showed the largest deviation when compared to depressive patients and normal people, increased significantly when viewed at 90fps, which was most effective in relieving depression. Artistic creations are bound to be accepted differently depending on the individual's perspective, but it is hoped that research that can improve the phenomenon of individuals suffering from depression by integrating artificial intelligence and traditional mental health approaches will be further developed and widely used for treatment.

• Nuclear Medicine and Molecular Imaging
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• v.43 no.5
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• pp.459-467
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• 2009

Purpose: The maximum likelihood-expectation maximization (ML-EM) is the statistical reconstruction algorithm derived from probabilistic model of the emission and detection processes. Although the ML-EM has many advantages in accuracy and utility, the use of the ML-EM is limited due to the computational burden of iterating processing on a CPU (central processing unit). In this study, we developed a parallel computing technique on GPU (graphic processing unit) for ML-EM algorithm. Materials and Methods: Using Geforce 9800 GTX+ graphic card and CUDA (compute unified device architecture) the projection and backprojection in ML-EM algorithm were parallelized by NVIDIA's technology. The time delay on computations for projection, errors between measured and estimated data and backprojection in an iteration were measured. Total time included the latency in data transmission between RAM and GPU memory. Results: The total computation time of the CPU- and GPU-based ML-EM with 32 iterations were 3.83 and 0.26 see, respectively. In this case, the computing speed was improved about 15 times on GPU. When the number of iterations increased into 1024, the CPU- and GPU-based computing took totally 18 min and 8 see, respectively. The improvement was about 135 times and was caused by delay on CPU-based computing after certain iterations. On the other hand, the GPU-based computation provided very small variation on time delay per iteration due to use of shared memory. Conclusion: The GPU-based parallel computation for ML-EM improved significantly the computing speed and stability. The developed GPU-based ML-EM algorithm could be easily modified for some other imaging geometries.

• Journal of Internet Computing and Services
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• v.16 no.2
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• pp.49-55
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• 2015

According to the statistics of traffic accidents over recent 5 years, traffic accidents during the night times happened more than the day times. There are various causes to occur traffic accidents and the one of the major causes is inappropriate or missing street lights that make driver's sight confused and causes the traffic accidents. In this paper, with smartphones, we designed and implemented a lane luminance measurement application which stores the information of driver's location, driving, and lane luminance into database in real time to figure out the inappropriate street light facilities and the area that does not have any street lights. This application is implemented under Native C/C++ environment using android NDK and it improves the operation speed than code written in Java or other languages. To measure the luminance of road, the input image with RGB color space is converted to image with YCbCr color space and Y value returns the luminance of road. The application detects the road lane and calculates the road lane luminance into the database sever. Also this application receives the road video image using smart phone's camera and improves the computational cost by allocating the ROI(Region of interest) of input images. The ROI of image is converted to Grayscale image and then applied the canny edge detector to extract the outline of lanes. After that, we applied hough line transform method to achieve the candidated lane group. The both sides of lane is selected by lane detection algorithm that utilizes the gradient of candidated lanes. When the both lanes of road are detected, we set up a triangle area with a height 20 pixels down from intersection of lanes and the luminance of road is estimated from this triangle area. Y value is calculated from the extracted each R, G, B value of pixels in the triangle. The average Y value of pixels is ranged between from 0 to 100 value to inform a luminance of road and each pixel values are represented with color between black and green. We store car location using smartphone's GPS sensor into the database server after analyzing the road lane video image with luminance of road about 60 meters ahead by wireless communication every 10 minutes. We expect that those collected road luminance information can warn drivers about safe driving or effectively improve the renovation plans of road luminance management.

• Korean Journal of Veterinary Research
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• v.41 no.3
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• pp.429-436
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• 2001

The present study was performed to investigate the effect of iohexol-ethanol mixture and barium-ethanol mixture on the induction of transcatheter renal artery embolization in healthy 18 dogs, which were divided into two groups of 9 dogs and the 9 dogs were divided into 3 subgroups of 3 dogs. The renal artery embolization was undertaken unilaterally with the dose of 1.5, 2.0, and 3.0 ml/kg iohexol-ehtanol mixture and with the dose of 0.2, 0.4, and 0.8 ml/kg barium-ethanol mixture. And serum chemistry on 0, 1,3, 7, and 14 days, intravenous pyelography on 7days, angiography on 14 days, and histopathology on 14 days were evaluated. Serum BUN and creatinine concentration of two groups with iohexol-ethanol mixture and barium-ethanol mixture administration were mildly increased a t 1 day after injection of embolic materials and then returned to baseline. No significant changes in BUN and creatinine levels occurred in any of dogs. In all dogs with the dose of 1.5 ml/kg iohexol-ethanol mixture, the renal arteries were not embolized. All dogs with the dose of 3.0 ml/kg died. In all dogs with the dose of 2.10 ml/kg, the treated arteries were completely occluded. In barium-ethanol mixture administered group, the renal artery in one dog with the dose of 0.2 ml/kg was not embolized. In all dogs with the dose of 0.8 ml/kg, the renal arteries were completely embolized, but loac overembolization occured in two dogs. All animals with the dose of 0.4 ml/kg had effective embolization and no evidence of radiopaque barium opacity in systemic arteries distal to the renal-artery was found. All embolized kidneys were shrunk and decreased in size in gross examination and were shown diffuse necrosis in histopathologic examination. In the present study, renal arteries were embolized with the dose of 2.0 ml/kg iohexol-ethanol mixture or 0.4 ml/kg barium-ethanol mixture. And it is considered that the dose had a satisfactory embolic effect.

• Geophysics and Geophysical Exploration
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• v.11 no.1
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• pp.52-59
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• 2008

We have developed a new deep-towed marine DC resistivity survey system. It was designed to detect the top boundary of the methane hydrate zone, which is not imaged well by seismic reflection surveys. Our system, with a transmitter and a 160-m-long tail with eight source electrodes and a receiver dipole, is towed from a research vessel near the seafloor. Numerical calculations show that our marine DC resistivity survey system can effectively image the top surface of the methane hydrate layer. A survey was carried out off Joetsu, in the Japan Sea, where outcrops of methane hydrate are observed. We successfully obtained DC resistivity data along a profile ${\sim}3.5\;km$ long, and detected relatively high apparent resistivity values. Particularly in areas with methane hydrate exposure, anomalously high apparent resistivity was observed, and we interpret these high apparent resistivities to be due to the methane hydrate zone below the seafloor. Marine DC resistivity surveys will be a new tool to image sub-seafloor structures within methane hydrate zones.

• Journal of Broadcast Engineering
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• v.23 no.1
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• pp.115-125
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• 2018

This paper presents a fast partition decision framework for High Efficiency Video Coding (HEVC) Screen Content Coding (SCC) based on machine learning. Currently, the HEVC performs quad-tree block partitioning process to achieve optimal coding efficiency. Since this process requires a high computational complexity of the encoding device, the fast encoding process has been studied as determining the block structure early. However, in the case of the screen content video coding, it is difficult to apply the conventional early partition decision method because it shows different partition characteristics from natural content. The proposed method solves the problem by classifying the screen content blocks after partition decision, and it shows an increase of 3.11% BD-BR and 42% time reduction compared to the SCC common test condition.